What is the "dropout" technique?
Dropout means that every individual data point is only used to fit a random subset of the neurons. This is done to make the neural network more like an ensemble model.

That is, just as a random forest is averaging together the results of many individual decision trees, you can see a neural network trained using dropout as averaging together the results of many individual neural networks (with 'results' understood to mean activations at every layer, rather than just the output layer).